Tracking control with aperiodic sampling over networks with delay and dropout

Abstract

This paper introduces a discrete-time technique for output feedback tracking control with aperiodic sampling over networks suffering delay and dropout. Introducing the concept of pseudo sampling, NCS is modelled as a linear parameter varying (LPV) system. Two methods are explained to obtain a convex approximation of the uncertainty region. It is clarified how to perform the approximation to have the uncertainty space as small as possible. Using this uncertainty space, a polytopic approximation is obtained for the LPV model. The approximated model is used to synthesise a controller for set-point tracking and disturbance rejection. An observer is also synthesised based on this model. The simplicity of the model together with a small uncertainty space, results in less conservative LMI conditions. Compared to the existing results, an improved tracking performance is obtained. The final value theorem for discrete-time LTI systems with constant sampling period is extended to time varying sampling periods. This theorem is used to design a feedforward gain for zero steady-state tracking of staircase reference signals.